code: def testPassingInLaplacePlusDefaultsIsSameAsLaplace(self):
      b = 10
      scale = rng.rand(b) + 0.5
      loc = rng.randn(b)
      lap = laplace.Laplace(loc=loc, scale=scale, validate_args=True)
      saslap = sinh_arcsinh.SinhArcsinh(
          loc=loc,
          scale=scale,
          distribution=laplace.Laplace(
              np.float64(np.zeros(b)), np.float64(1)
          ),
          validate_args=True,
      )
  
      x = rng.randn(5, b)
      lap_pdf, saslap_pdf = self.evaluate([lap.prob(x), saslap.prob(x)])
      self.assertAllClose(lap_pdf, saslap_pdf)
  
      lap_samps, saslap_samps = self.evaluate(
          [
              lap.sample(10000, seed=test_util.test_seed()),
              saslap.sample(10000, seed=test_util.test_seed()),
          ]
      )
      self.assertAllClose(loc, saslap_samps.mean(axis=0), atol=0.1)
      self.assertAllClose(
          lap_samps.mean(axis=0), saslap_samps.mean(axis=0), atol=0.1
      )
      self.assertAllClose(
          lap_samps.std(axis=0), saslap_samps.std(axis=0), atol=0.1
      )
  
file_path: probability/tensorflow_probability/python/distributions/sinh_arcsinh_test.py
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import laplace
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sinh_arcsinh
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 4 for calling the SinhArcsinhTest obj's underlying member method code with example usage: obj.testPassingInLaplacePlusDefaultsIsSameAsLaplace() without return types